Imagine bringing on a new employee who works around the clock, processes millions of data points instantly, and never overlooks a single detail in your pricing strategy. It sounds impressive, doesn’t it? That is, until they start making decisions you can’t explain and fail to adapt to the nuances of your business.
The truth is that artificial intelligence (AI) agents hold much promise. But they also pose risks when deployed haphazardly. Instead of rushing to implement AI agents, businesses need to make sure their agents act with clarity, purpose, and accountability. As this technology becomes more integral to everyone’s day-to-day work, companies need to set clear principles so that AI agents don’t just act fast, but act in ways that make sense for the business and the people behind it. Without these guardrails, AI agents risk becoming unpredictable, misaligned black boxes.
At PROS, we approach agentic AI with intentionality, rooted in decades of experience delivering AI-powered solutions. The PROS framework for Agentic AI is built on six foundational principles that ensure agents are not only capable but credible.
The Six Guiding Principles
Agentic AI at PROS is grounded in six core principles that shape how we design our agents and how our customers deploy them. These principles are not merely aspirational; they are embedded in the architecture and behavior of every PROS agent.
Without further ado, the six guiding principles are as follows:
- Built for People: Every agent is designed to blend into natural business workflows to ensure a seamless experience, not a forced bolt-on. This ensures that business users get the right help at the right time – in context, to augment, not replace.
- Goal-Oriented: Every agent is created to pursue a specific, measurable business outcome versus simply executing a task. For example, PROS AI agents are purpose-built to achieve goals like accelerating quote creation time, surfacing the right price or product recommendation, and generating the right visualization.
- Autonomous: PROS AI agents are designed to operate independently within defined parameters, reducing the administrative and time-consuming tasks human users usually would need to undertake themselves. This autonomy is key to achieving speed and scale in modern selling environments.
- Adaptive: The commercial environment and broader world we live in are in constant flux. As PROS AI agents continue to evolve, they will learn from, and respond to changes in real time, such as market shifts and customer signals, ensuring relevance and responsiveness at every step. Moving beyond task automation and into more complex optimization outcomes – across both pricing and quoting dimensions.
- Trustworthy: In order to be trusted, Agents need to be transparent, ethical, and accurate. Part of the beauty of LLMs and agentic flows is their creative ability. However, proper checks and balances need to be baked in to ensure that “answers” are credible and within the bounds of tolerance. Our PROS Agents combine the predictive AI with LLM-based AI to ensure the results are business-ready.
- Enterprise-Grade: Built for businesses, PROS AI agents are designed to meet the scalability, security, and performance demands of global enterprises. Deploying and supporting production Agents in our platform requires the same commitment that we’ve always offered our customers – backed by our SLA. This isn’t consumer AI dressed up for business; it’s purpose-built technology for commerce.
Together, these principles ensure that PROS AI agents aren’t just technically capable but are also aligned with business goals, scalable, and, most importantly, trustworthy.
Acting With Humans, Not Instead of Them
PROS agents are designed to augment human effort, not replace it. They help surface predictions, guide smarter decisions, and boost productivity across roles and workflows. Rather than waiting for input, agents proactively flag which offers need attention to help users focus on the tasks that matter the most, freeing up mental space so users can make smarter moves, faster.
By combining conversational interfaces powered by large language models (LLMs) and predictive AI that can detect patterns based on data, PROS AI agents work alongside human users to co-create offers and solutions that balance strategic goals and operational constraints.
For example, one of our travel agents, the GSO Task Agent, helps airline personnel determine high priority offers and get them to market quickly and accurately. By analyzing information such as the nearest expiration or due dates, the size of the group, the potential group booking total, and more, users never have to worry about missing an opportunity to close the deal.
It’s not about handing over complete control; it’s about giving workers the right support at the right time to help them do their jobs better.
The Right Balance of Autonomy & Oversight
While agents can perform many tasks independently, they are designed to work in collaboration with the people they serve – embracing a “human-in the loop” philosophy. Within each session, agents adapt to user inputs and context to build trust and enable both the AI and the user to work more effectively together.
Take the industrial manufacturing industry, for example. The Pricing Agent focuses on identifying patterns in pricing data that suggest potential misalignment, such as unusually high discounts on certain products. When such behavior is detected, the agent flags the relevant items and notifies pricing managers, enabling them to investigate and take appropriate action.
This balance of automation and human oversight ensures agents deliver real business value, without sacrificing control or accountability.
Over time, as trust in this technology grows and capabilities advance, we will see a natural progression from AI-assisted to AI-augmented, and eventually to AI-led workstreams. Today, agents primarily assist humans with their current tasks. Soon agents will augment humans to accomplish more tasks together, and, ultimately, agents will lead workstreams on their own.
Blending Large Language and Numerical (Predictive) Models
To feel comfortable using any kind of AI, we know that users want to always be able to understand when and how an AI agent will act. PROS understands this and has blended two different models to deliver the best of both worlds: natural language interaction and reasoning ability from the large language models (LLMs), and stable, deterministic recommendations from PROS predictive models.
While LLMs thrive on variability to make interactions natural and engaging (mirroring how humans communicate), this unpredictability can cause outcomes that vary based on user prompts and contexts, etc., and can be undesirable for tasks that require strategic, prescriptive outcomes. For example, pricing requires accuracy and repeatability. Businesses need outputs grounded in data, not hallucinations.
Predictive AI delivers repeatable responses based on specific inputs that are used to train a neural-network model. This is useful for areas like price optimization, demand forecasting, and capacity optimization where precision and accuracy are required. Agents can then consume those outputs to guide actions or enhance the user experience.
By bringing together predictive AI models with LLM models, Agents can provide the natural language interface that users desire while better handling ambiguity using predictive AI. This is ideal for systems needing adaptability, creativity, and probabilistic reasoning, such as recommendation engines that respond to buyer intent signals or dynamic pricing algorithms that adjust in real time based on market demand.
For instance, a recommendation engine might use an LLM model to surface relevant options based on predictive AI that has already determined the best-fit options based on the probability to purchase.
At PROS, this balance is built into our agents by design. By blending predictive models with language models, PROS AI agents are both easy to use and more accurate for the business.
Building the Future With Agentic AI, the PROS Way
As it stands today, companies of all sizes have begun to adopt Agents that are providing added value to a variety of tasks and workers’ needs. Within the next two years, businesses will become increasingly comfortable adopting more AI to fuel even more critical business processes.
We’re still in the early days of agentic AI – as agent technology matures, including memory optimization & accuracy, the value will only continue to rise. Workers will be able to seamlessly dispatch a network of agents to help them achieve both short-term and long-term goals. Not only will this boost productivity, but it will also allow individuals to accelerate their careers. This journey from AI assistance to AI augmentation will empower teams to focus on more creative and strategic work.
The future of AI is not just about doing things faster but about unlocking new opportunities and enabling global growth. Download the PROS Agent Framework today to see how these guiding principles can be operationalized to meet your enterprise’s goals.
Download PROS Agent Framework.
